Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare this a safe idempotent read, so the description correctly spends its budget on methodology instead: distinct-wallet counting versus daily average, fee/royalty figures computed only over sales with recorded splits and reported with coverage, and self-trade exclusion. That is exactly the context needed to interpret the numbers. It stops short of stating data freshness, update cadence, or rate limits, which keeps it off a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Effectively one front-loaded sentence that leads with the scope and window, then the metric list, then the caveats. The nested parentheticals about distinct-wallet counting and split coverage are dense but each carries real information, so little is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of describing the response and does so thoroughly: top-level sales/volume/participants plus a per-marketplace breakdown with fees, royalties, and coverage. An agent knows what it will get back and how to read it; only freshness and numeric formatting are unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the sole parameter already has a description, default, and min/max bounds. The description repeats the accepted values '7, 30, 90 or 365 days' without adding interpretation, so the schema remains the primary source — the baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource and scope: the Cardano NFT market in aggregate over a selectable window, enumerating the metrics returned (sales, volume in ADA, buyers/sellers, per-marketplace breakdown). The word 'whole' and the per-marketplace breakdown implicitly distinguish it from collection-level siblings like get_nft_collection or get_nft_analytics, but no sibling is named.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description frames usage by content ('whole market overview') but never says when to pick this over get_nft_analytics, get_nft_collection, or get_market_overview, nor does it state prerequisites or exclusions. The agent must infer the choice from the aggregate-vs-collection framing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.